The world population is ageing and while many older people are in good health, others have increasing numbers of comorbidities. The presence of multiple health conditions can raise methodological challenges when modelling health care interventions. One instance is when determining the effect on the underlying health related quality of life when alleviating or avoiding a particular condition. Historically, health care modellers have estimated the preference-based utility values required for the comorbidity using the utility values obtained from cohorts with the individual conditions. Research conducted within HEDS has shown that the alternative methods typically used produce very different utility values.
Research in this area is
continuing to be developed within HEDS and a project funded by
Bristol-Myers Squibb Pharmaceuticals Limited will examine alternative
methods of predicting the effects on quality of life due to
comorbidities. The proposed approach will examine the use of response
mapping to predict the preference-based utility values for
comorbidities. Unlike the methods typically used, which combine the
overall summary preference-based utility values, response mapping
utilises all the knowledge and information from across the full health
profile using data from the health dimensions. Due for completion at
the end of this year, the results of this research will contribute to
the sparse literature in this area and is expected to identify
additional research questions.
Roberta Ara is leading this research project.
Photo credit: xavi talleda via Flickr Creative Commons